Review: Dystroglycan in the Nervous System

Dystroglycan is part of a large complex of proteins, the dystrophin-glycoprotein complex, which has been implicated in the pathogenesis of muscular dystrophies for a long time. Besides muscular degeneration many patients manifest symptoms of neurological and cognitive dysfunction. Newer findings suggest that dystroglycan is implicated in brain development, synapse formation and plasticity, nerve-glia interactions and maintenance of the blood-brain barrier.
Most research so far has focused on the functions of dystroglycan in muscle and neuromuscular junctions, while its role in the brain and interneuronal synapses has been largely neglected. 
This review will give an overview of the biochemistry of dystroglycan, its interaction with other proteins as well as its confirmed and hypothetical functions in the nervous system in health and diesease

Extracting conclusion sections from PubMed abstracts for rapid key assertion integration in biomedical research

Key assertions are extracted from “conclusions” sections of PubMed abstracts and
converted into Semantic Web / Linked Data format. The results are made accessible via
files, a SPARQL endpoint, and a faceted search interface. Conclusion sections are
identified as valuable resources for machine-augmented key assertion identification and
integration in the biomedical domain. Results are discussed and opportunities for future
work and cooperation are highlighted.
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Establishing a distributed system for the simple representation and integration of diverse scientific assertions

<p>Abstract</p> <p>Background</p> <p>Information technology has the potential to increase the pace of scientific progress by helping researchers in formulating, publishing and finding information. There are numerous projects that employ ontologies and Semantic Web technologies towards this goal. However, the number of applications that have found widespread use among biomedical researchers is still surprisingly small. In this paper we present the aTag (‘associative tags’) convention, which aims to drastically lower the entry barriers to the biomedical Semantic Web. aTags are short snippets of HTML+RDFa with embedded RDF/OWL based on the Semantically Interlinked Online Communities (SIOC) vocabulary and domain ontologies and taxonomies, such as the Open Biomedical Ontologies and DBpedia. The structure of aTags is very simple: a short piece of human-readable text that is ‘tagged’ with relevant ontological entities. This paper describes our efforts for seeding the creation of a viable ecosystem of datasets, tools and services around aTags.</p> <p>Results</p> <p>Numerous biomedical datasets in aTag format and systems for the creation of aTags have been set-up and are described in this paper. Prototypes of some of these systems are accessible at <url>http://hcls.deri.org/atag</url></p> <p>Conclusions</p> <p>The aTags convention enables the rapid development of diverse, integrated datasets and semantically interoperable applications. More work needs to be done to study the practicability of this approach in different use-case scenarios, and to encourage uptake of the convention by other groups.</p